feat(lidar): add dataset gateway boundary
This commit is contained in:
DCCONSTRUCTIONS
@@ -0,0 +1,243 @@
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export type DatasetRepresentationId =
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| "native-scan"
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| "normalized-scan"
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| "rolling-local-map";
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export interface DatasetGatewayCatalog {
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storage: {
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configured: boolean;
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admitted: boolean;
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status: "ready" | "blocked-storage-policy";
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requiredWindowsRoot: string;
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requiredWslRoot: string;
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};
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source: {
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sourceId: string;
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displayName: string;
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role: string;
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license: string;
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format: string;
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frameSemantics: "one-lidar-revolution";
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platforms: string[];
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superclasses: string[];
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validationArchiveGb: number;
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admissionStatus: "ready-for-download" | "blocked-storage-policy";
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};
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representations: Array<{
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id: DatasetRepresentationId;
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title: string;
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purpose: string;
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accumulation: boolean;
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}>;
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pipeline: Array<{
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stage: string;
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requires: string[];
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produces: string;
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}>;
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currentInput: {
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representation: "vendor-mapped-increment";
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nativeScan: false;
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perPointTime: false;
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ringOrLine: false;
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admittedForPatchworkpp: false;
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reason: string;
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};
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nextAction: string;
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}
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export class DatasetGatewayContractError extends Error {}
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type DatasetFetch = (
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input: RequestInfo | URL,
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init?: RequestInit,
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) => Promise<Response>;
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const SAFE_ID = /^[a-z0-9][a-z0-9._:/-]{0,159}$/;
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function record(value: unknown, label: string): Record<string, unknown> {
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if (!value || typeof value !== "object" || Array.isArray(value)) {
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throw new DatasetGatewayContractError(`${label}: ожидался объект`);
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}
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return value as Record<string, unknown>;
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}
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function array(value: unknown, label: string): unknown[] {
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if (!Array.isArray(value)) {
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throw new DatasetGatewayContractError(`${label}: ожидался массив`);
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}
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return value;
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}
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function string(value: unknown, label: string, safe = false): string {
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if (
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typeof value !== "string"
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|| !value
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|| (safe && !SAFE_ID.test(value))
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) {
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throw new DatasetGatewayContractError(`${label}: некорректная строка`);
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}
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return value;
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}
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function strings(value: unknown, label: string): string[] {
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return array(value, label).map((item, index) =>
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string(item, `${label}[${index}]`, true)
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);
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}
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function displayStrings(value: unknown, label: string): string[] {
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return array(value, label).map((item, index) =>
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string(item, `${label}[${index}]`)
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);
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}
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function boolean(value: unknown, label: string): boolean {
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if (typeof value !== "boolean") {
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throw new DatasetGatewayContractError(`${label}: ожидался boolean`);
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}
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return value;
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}
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function number(value: unknown, label: string): number {
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if (typeof value !== "number" || !Number.isFinite(value) || value < 0) {
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throw new DatasetGatewayContractError(`${label}: некорректное число`);
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}
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return value;
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}
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export function parseDatasetGatewayCatalog(
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value: unknown,
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): DatasetGatewayCatalog {
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const source = record(value, "Dataset Gateway");
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if (
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source.schema_version !== "missioncore.dataset-gateway-catalog/v1"
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|| source.access !== "read-only"
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) {
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throw new DatasetGatewayContractError("Dataset Gateway contract несовместим");
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}
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const storage = record(source.storage, "storage");
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const storageStatus = storage.status;
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if (storageStatus !== "ready" && storageStatus !== "blocked-storage-policy") {
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throw new DatasetGatewayContractError("storage.status: неизвестное значение");
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}
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if (storage.path_exposed !== false) {
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throw new DatasetGatewayContractError("Dataset Gateway раскрыл локальный путь");
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}
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const sources = array(source.sources, "sources");
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if (sources.length !== 1) {
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throw new DatasetGatewayContractError("Ожидался один первичный dataset source");
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}
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const dataset = record(sources[0], "sources[0]");
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const download = record(dataset.download, "source.download");
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const admission = record(dataset.admission, "source.admission");
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if (download.automatic !== false) {
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throw new DatasetGatewayContractError("Большой dataset нельзя загружать автоматически");
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}
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const admissionStatus = admission.status;
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if (
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admissionStatus !== "ready-for-download"
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&& admissionStatus !== "blocked-storage-policy"
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) {
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throw new DatasetGatewayContractError("source admission status неизвестен");
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}
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const representations = array(
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source.representations,
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"representations",
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).map((value, index) => {
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const item = record(value, `representations[${index}]`);
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const id = item.id;
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if (
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id !== "native-scan"
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&& id !== "normalized-scan"
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&& id !== "rolling-local-map"
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) {
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throw new DatasetGatewayContractError("Неизвестная LiDAR representation");
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}
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const normalizedId: DatasetRepresentationId = id;
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return {
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id: normalizedId,
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title: string(item.title, "representation.title"),
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purpose: string(item.purpose, "representation.purpose", true),
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accumulation: boolean(item.accumulation, "representation.accumulation"),
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};
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});
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const pipeline = array(source.pipeline, "pipeline").map((value, index) => {
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const item = record(value, `pipeline[${index}]`);
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return {
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stage: string(item.stage, "pipeline.stage", true),
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requires: strings(item.requires, "pipeline.requires"),
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produces: string(item.produces, "pipeline.produces", true),
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};
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});
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const inputs = array(source.known_inputs, "known_inputs");
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const currentInput = record(inputs[0], "known_inputs[0]");
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if (
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currentInput.representation !== "vendor-mapped-increment"
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|| currentInput.native_scan !== false
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|| currentInput.per_point_time !== false
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|| currentInput.ring_or_line !== false
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|| currentInput.admitted_for_patchworkpp !== false
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) {
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throw new DatasetGatewayContractError("Vendor-map boundary завышен");
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}
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if (dataset.frame_semantics !== "one-lidar-revolution") {
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throw new DatasetGatewayContractError("GOOSE frame semantics несовместима");
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}
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return {
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storage: {
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configured: boolean(storage.configured, "storage.configured"),
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admitted: boolean(storage.admitted, "storage.admitted"),
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status: storageStatus,
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requiredWindowsRoot: string(
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storage.required_windows_root,
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"storage.required_windows_root",
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),
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requiredWslRoot: string(storage.required_wsl_root, "storage.required_wsl_root"),
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},
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source: {
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sourceId: string(dataset.source_id, "source_id", true),
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displayName: string(dataset.display_name, "display_name"),
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role: string(dataset.role, "role", true),
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license: string(dataset.license, "license"),
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format: string(dataset.format, "format", true),
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frameSemantics: "one-lidar-revolution",
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platforms: displayStrings(dataset.platforms, "platforms"),
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superclasses: strings(dataset.superclasses, "superclasses"),
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validationArchiveGb: number(
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download.validation_archive_gb,
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"validation_archive_gb",
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),
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admissionStatus,
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},
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representations,
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pipeline,
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currentInput: {
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representation: "vendor-mapped-increment",
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nativeScan: false,
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perPointTime: false,
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ringOrLine: false,
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admittedForPatchworkpp: false,
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reason: string(currentInput.reason, "known_inputs.reason", true),
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},
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nextAction: string(source.next_action, "next_action", true),
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};
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}
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async function responseJson(response: Response): Promise<unknown> {
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if (!response.ok) {
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throw new Error(`Dataset Gateway HTTP ${response.status}`);
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}
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return response.json();
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}
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export async function fetchDatasetGatewayCatalog(
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options: { signal?: AbortSignal; fetcher?: DatasetFetch } = {},
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): Promise<DatasetGatewayCatalog> {
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const fetcher = options.fetcher ?? fetch;
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const response = await fetcher("/api/v1/lidar/dataset-gateway", {
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method: "GET",
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headers: { Accept: "application/json" },
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signal: options.signal,
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});
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return parseDatasetGatewayCatalog(await responseJson(response));
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}
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@@ -137,6 +137,17 @@
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}
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@media (max-width: 760px) {
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.dataset-gateway__representations,
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.dataset-gateway__grid,
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.dataset-gateway__footer {
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grid-template-columns: 1fr;
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}
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.dataset-gateway__representations > div + div {
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border-top: 1px solid rgb(255 255 255 / 0.07);
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border-left: 0;
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}
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.control-station .nodedc-header__profile-button {
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display: none;
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}
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@@ -807,6 +807,144 @@
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gap: 1rem;
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}
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.dataset-gateway {
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display: grid;
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gap: 1rem;
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overflow: hidden;
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border: 1px solid color-mix(in srgb, var(--nodedc-accent) 24%, transparent);
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background:
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radial-gradient(circle at 10% 0%, color-mix(in srgb, var(--nodedc-accent) 10%, transparent), transparent 32%),
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rgb(255 255 255 / 0.025);
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}
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.dataset-gateway__heading p,
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.dataset-gateway__grid p,
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.dataset-gateway__pending {
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margin: 0.4rem 0 0;
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color: var(--nodedc-text-muted);
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font-size: 0.68rem;
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line-height: 1.55;
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}
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.dataset-gateway__representations {
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display: grid;
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grid-template-columns: repeat(3, minmax(0, 1fr));
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overflow: hidden;
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border: 1px solid rgb(255 255 255 / 0.07);
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border-radius: 0.9rem;
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}
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.dataset-gateway__representations > div {
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position: relative;
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display: grid;
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min-height: 7.4rem;
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align-content: center;
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gap: 0.3rem;
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padding: 1rem 1.1rem 1rem 3.6rem;
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background: rgb(255 255 255 / 0.025);
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}
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.dataset-gateway__representations > div + div {
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border-left: 1px solid rgb(255 255 255 / 0.07);
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}
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.dataset-gateway__representations > div > span {
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position: absolute;
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top: 1rem;
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left: 1rem;
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color: var(--nodedc-accent);
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font-size: 0.62rem;
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letter-spacing: 0.14em;
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}
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.dataset-gateway__representations strong,
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.dataset-gateway__representations small,
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.dataset-gateway__representations em {
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display: block;
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}
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.dataset-gateway__representations strong {
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color: var(--nodedc-text-primary);
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font-size: 0.76rem;
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}
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.dataset-gateway__representations small,
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.dataset-gateway__representations em {
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color: var(--nodedc-text-muted);
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font-size: 0.58rem;
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line-height: 1.35;
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}
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.dataset-gateway__representations em {
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color: color-mix(in srgb, var(--nodedc-accent) 72%, white);
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font-style: normal;
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}
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.dataset-gateway__grid {
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display: grid;
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grid-template-columns: repeat(2, minmax(0, 1fr));
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gap: 0.7rem;
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}
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.dataset-gateway__grid > section {
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min-width: 0;
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padding: 1rem;
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border: 1px solid rgb(255 255 255 / 0.07);
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border-radius: 0.9rem;
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background: rgb(255 255 255 / 0.02);
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}
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.dataset-gateway__grid > section[data-warning="true"] {
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border-color: rgb(255 181 71 / 0.2);
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}
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.dataset-gateway__grid h3 {
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margin: 0.28rem 0 0;
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color: var(--nodedc-text-primary);
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font-size: 1rem;
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}
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.dataset-gateway__facts {
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display: flex;
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flex-wrap: wrap;
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gap: 0.35rem;
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margin-top: 0.8rem;
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}
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.dataset-gateway__facts span {
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padding: 0.32rem 0.5rem;
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border-radius: 999px;
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background: rgb(255 255 255 / 0.045);
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color: var(--nodedc-text-secondary);
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font-size: 0.56rem;
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}
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.dataset-gateway__footer {
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display: grid;
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grid-template-columns: minmax(0, 0.8fr) minmax(0, 1.2fr);
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gap: 1rem;
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padding-top: 0.85rem;
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border-top: 1px solid rgb(255 255 255 / 0.07);
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}
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.dataset-gateway__footer > div {
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display: grid;
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gap: 0.2rem;
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min-width: 0;
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}
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.dataset-gateway__footer span,
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.dataset-gateway__footer small {
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color: var(--nodedc-text-muted);
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font-size: 0.58rem;
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}
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.dataset-gateway__footer strong {
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overflow-wrap: anywhere;
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color: var(--nodedc-text-primary);
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font-size: 0.68rem;
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}
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.lidar-quality-message {
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display: grid;
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min-height: 12rem;
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@@ -0,0 +1,133 @@
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import { useEffect, useState } from "react";
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import { GlassSurface, StatusBadge } from "@nodedc/ui-react";
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import {
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fetchDatasetGatewayCatalog,
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type DatasetGatewayCatalog,
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} from "../core/lidar/datasetGateway";
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const representationLabels: Record<string, string> = {
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"native-scan": "Один оборот / скан",
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"normalized-scan": "Deskew + bounded cleanup",
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"rolling-local-map": "Pose + TTL + voxel map",
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};
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export function DatasetGatewayPanel() {
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const [catalog, setCatalog] = useState<DatasetGatewayCatalog | null>(null);
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const [error, setError] = useState<string | null>(null);
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useEffect(() => {
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const controller = new AbortController();
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void fetchDatasetGatewayCatalog({ signal: controller.signal })
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.then((value) => {
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if (!controller.signal.aborted) setCatalog(value);
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})
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.catch((loadError: unknown) => {
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if (controller.signal.aborted) return;
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setError(
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loadError instanceof Error
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? loadError.message
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: "Dataset Gateway недоступен",
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);
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});
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return () => controller.abort();
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}, []);
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return (
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<GlassSurface className="dataset-gateway" padding="lg">
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<header className="panel-heading dataset-gateway__heading">
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<div>
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<span className="section-eyebrow">DATASET GATEWAY · S0</span>
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<h2>Три разных LiDAR-продукта</h2>
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<p>
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Кольцевой одиночный скан, очищенный sensor-frame и накопленная карта
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больше не считаются одним облаком.
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</p>
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</div>
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<StatusBadge
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tone={error ? "danger" : catalog?.storage.admitted ? "success" : "warning"}
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>
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{error
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? "Gateway недоступен"
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: catalog?.storage.admitted
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? "D: допущен"
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: "Ожидает D:"}
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</StatusBadge>
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</header>
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{catalog ? (
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<>
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<div className="dataset-gateway__representations">
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{catalog.representations.map((representation, index) => (
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<div key={representation.id}>
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<span>0{index + 1}</span>
|
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<strong>
|
||||
{representationLabels[representation.id] ?? representation.title}
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||||
</strong>
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<small>{representation.title}</small>
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<em>
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{representation.accumulation
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||||
? "накопление включено явно"
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||||
: "без накопления"}
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</em>
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||||
</div>
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||||
))}
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||||
</div>
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||||
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||||
<div className="dataset-gateway__grid">
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<section>
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<span className="section-eyebrow">ПЕРВЫЙ BASELINE</span>
|
||||
<h3>{catalog.source.displayName}</h3>
|
||||
<p>
|
||||
Один оборот VLS-128 в SemanticKITTI XYZI + point-wise semantic и
|
||||
instance labels. Это то самое разреженное кольцевое облако,
|
||||
которое корректно сравнивать с алгоритмами.
|
||||
</p>
|
||||
<div className="dataset-gateway__facts">
|
||||
<span>{catalog.source.platforms.join(" · ")}</span>
|
||||
<span>{catalog.source.superclasses.length} superclasses</span>
|
||||
<span>val {catalog.source.validationArchiveGb} ГБ</span>
|
||||
<span>{catalog.source.license}</span>
|
||||
</div>
|
||||
</section>
|
||||
<section data-warning="true">
|
||||
<span className="section-eyebrow">ТЕКУЩИЙ DEVICE INPUT</span>
|
||||
<h3>Mapped feed ≠ raw scan</h3>
|
||||
<p>
|
||||
Внешний MQTT содержит vendor-mapped increment после LIO. В нём
|
||||
нет per-point time и line/ring, поэтому из него нельзя честно
|
||||
восстановить один исходный скан или выполнить deskew.
|
||||
</p>
|
||||
<div className="dataset-gateway__facts">
|
||||
<span>Patchwork++: diagnostic only</span>
|
||||
<span>rolling map: возможно</span>
|
||||
<span>raw reconstruction: невозможно</span>
|
||||
</div>
|
||||
</section>
|
||||
</div>
|
||||
|
||||
<footer className="dataset-gateway__footer">
|
||||
<div>
|
||||
<span>Storage gate</span>
|
||||
<strong>{catalog.storage.requiredWindowsRoot}</strong>
|
||||
<small>{catalog.storage.requiredWslRoot}</small>
|
||||
</div>
|
||||
<div>
|
||||
<span>Следующий исполнимый шаг</span>
|
||||
<strong>
|
||||
{catalog.storage.admitted
|
||||
? "Скачать GOOSE validation и импортировать первый кадр"
|
||||
: "Подключить Dataset Root на D: worker"}
|
||||
</strong>
|
||||
<small>Автозагрузка 3.3 ГБ намеренно запрещена</small>
|
||||
</div>
|
||||
</footer>
|
||||
</>
|
||||
) : (
|
||||
<p className="dataset-gateway__pending">
|
||||
{error ?? "Читаем входные контракты Dataset Gateway…"}
|
||||
</p>
|
||||
)}
|
||||
</GlassSurface>
|
||||
);
|
||||
}
|
||||
@@ -26,6 +26,7 @@ import {
|
||||
LidarGroundPointCloud,
|
||||
type LidarGroundViewMode,
|
||||
} from "./LidarGroundPointCloud";
|
||||
import { DatasetGatewayPanel } from "./DatasetGatewayPanel";
|
||||
|
||||
function formatNumber(value: number | null, digits = 1): string {
|
||||
if (value === null) return "—";
|
||||
@@ -220,6 +221,8 @@ export function LidarQualityWorkspace({
|
||||
<span className="workspace-lead__note">Только проверенные replay-артефакты</span>
|
||||
</section>
|
||||
|
||||
<DatasetGatewayPanel />
|
||||
|
||||
{loading && !detail ? (
|
||||
<GlassSurface className="lidar-quality-message" padding="lg">
|
||||
<StatusBadge tone="accent">Проверка evidence</StatusBadge>
|
||||
|
||||
Reference in New Issue
Block a user